Model risk management

Use our best-in-class methodologies and expertise to meet model risk management and regulatory requirements

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Meet model risk governance requirements

As the use and complexity of credit risk models have grown over the years, so have regulatory demands — making model risk management a priority for organizations. Back testing, benchmarking, sensitivity analysis and stress testing services can help organizations ensure model integrity while providing transparency and necessary documentation.

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Get an independent, third-party review

Ensure regulatory compliance with a third-party audit to support your model risk governance needs. Our consulting and modeling teams can provide your organization with a review of your model risk management practices and assist with audit preparations.

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Receive best recommendations from experts

Leveraging best-in-class methodologies, our experts will conduct an in-depth review of your risk exposures, business activities and the complexity and extent of model use to provide a comprehensive gap analysis of your current validation processes and make recommendations as needed.  The gap analysis identifies discrepancies between current actions and regulatory requirements, such as model documentation and specifications, implementation standards and protocols, consistency of model assumptions with utilizations, and value and usage of monitoring reports.


Model risk is a type of risk that arises from the potential inaccuracies, errors or misuse associated with the credit risk models used in decisioning. These models, typically created for forecasting and simulating potential scenarios, are based on certain data, assumptions and calculations. However, if these assumptions are incorrect or the calculations are erroneous, it can lead to inaccurate predictions and undesirable financial outcomes. This is what is referred to as 'model risk'.

Model risk management is a subset of risk management that focuses on managing the risks associated with the use of models in business decision-making strategies. It involves identifying and mitigating the risks associated with using these models, which can include implementing rigorous validation processes and monitoring the performance of the models over time to identify drift. It also encompasses regulatory aspects of model governance. 

Effective model risk management can reduce the possibility of financial losses, reputational damage and/or incompliance with regulatory requirements due to the use of inaccurate or misused models. Financial institutions that use models in their decisioning processes must ensure that their policies and procedures are consistent with the guidance provided by the Federal Reserve Board (FRB) and the Office of the Comptroller of the Currency (OCC).


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